Advanced Machine Learning Techniques for Predicting Nha Trang Shorelines by Cheng Yin, Le Thanh Binh, Duong Tran Anh, Son T. Mai, Anh Le, Van-Hau Nguyen, Van-Chien Nguyen, Nguyen Xuan Tinh, Hitoshi Tanaka, Nguyen Trung Viet, Long D. Nguyen, Trung Q. Duong

“…In this paper, we explored a statistical forecasting model, Seasonal Auto-regressive Integrated Moving Average (SARIMA), and two Machine Learning (ML) models, Neural Network Auto-Regression (NNAR) and Long Short-Term Memory (LSTM), to predict the shoreline variations from surveillance camera images. …”
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GeoViT: Mixed-Scale Transformer for Perspective Correction in Print-Cam Image Watermarking by Said Boujerfaoui, Anass Mancour-Billah, Hassan Douzi, Rachid Harba

“…Our method significantly outperforms existing approaches in geometric accuracy, visual fidelity, and perceptual quality. …”
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Machine learning prediction of 18 date palm polyphenol protection against biomolecular damage by Nashi K. Alqahtani, Tareq M. Alnemr, Rania Ismail, Hosam M. Habib

“…This highlights targeted method improvements. These findings demonstrate that certain date components offer higher specific bioactivity, and the ML approach validates these methods, revealing benefits and limitations. …”
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Estimating Maize Leaf Water Content Using Machine Learning with Diverse Multispectral Image Features by Yuchen Wang, Jianliang Wang, Jiayue Li, Jiacheng Wang, Hanzeyu Xu, Tao Liu, Juan Wang

“…By extracting vegetation indices, image coverage, and texture features and integrating them with ground-truth data, the study examines the variation in LWC estimation accuracy across different growth stages. …”
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YOLO-SBA: A Multi-Scale and Complex Background Aware Framework for Remote Sensing Target Detection by Yifei Yuan, Yingmei Wei, Xiaoyan Zhou, Yanming Guo, Jiangming Chen, Tingshuai Jiang

“…Our proposed YOLO-SBA first processes the input through the Multi-Branch Attention Feature Fusion Module (MBAFF) to extract global contextual dependencies and local detail features. It then integrates these features using the Bilateral Attention Feature Mixer (BAFM) for efficient fusion, enhancing the saliency of multi-scale target features to tackle target scale variations. …”
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Sustainability of evidence based interventions implemented in CDC’s colorectal cancer control program by Krishna P. Sharma, Amy DeGroff, Michele Beckman, Sun Juzhong, Coleman King Sallyann, Joseph Djenaba

“…Results The results highlighted significant variations in the sustainability of different EBIs. …”
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Bee Bread Drying Process Intensification in Combs Using Solar Energy by Daulet Toibazar, Baydaulet Urmashev, Aliya Tursynzhanova, Vladimir Nekrashevich, Indira Daurenova, Adilkhan Niyazbayev, Kanat Khazimov, Francesco Pegna, Marat Khazimov

“…The research methodology integrates both numerical simulation and experimental investigation. …”
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Object-Level Contrastive-Learning-Based Multi-Branch Network for Building Change Detection from Bi-Temporal Remote Sensing Images by Shiming Li, Fengtao Yan, Cheng Liao, Qingfeng Hu, Kaifeng Ma, Wei Wang, Hui Zhang

“…Our approach achieves IoU values of 88.54% and 51.94%, respectively, surpassing state-of-the-art methods for building change detection.…”
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Peatland pixel-level classification via multispectral, multiresolution and multisensor data using convolutional neural network by Luca Zelioli, Fahimeh Farahnakian, Maarit Middleton, Timo P. Pitkänen, Sakari Tuominen, Paavo Nevalainen, Jonne Pohjankukka, Jukka Heikkonen

“…The core strategy of our method involves a late fusion architecture that seamlessly integrates multi-source remote sensing (RS) data, including optical imagery, synthetic aperture radar (SAR), airborne laser scanning (ALS), and multi-source national forest inventory (MS-NFI) datasets. …”
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The Kernel Density Estimation Technique for Spatio-Temporal Distribution and Mapping of Rain Heights over South Africa: The Effects on Rain-Induced Attenuation by Yusuf Babatunde Lawal, Pius Adewale Owolawi, Chunling Tu, Etienne Van Wyk, Joseph Sunday Ojo

“…The kernel density estimation (KDE) method was applied to estimate the temporal variation of rain height. …”
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Magnetic Induction Spectroscopy-Based Non-Contact Assessment of Avocado Fruit Condition by Tianyang Lu, Adam D. Fletcher, Richard John Colgan, Michael D. O’Toole

“…Through this approach, the sample set was classified into three categories, each corresponding to distinct conductivity variation patterns.…”
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Underwater optical metrology for precision monitoring of marine habitats: the MANATEE project by E. Nocerino, E. Nocerino, F. Menna, A. Calantropio, F. Pinna, S. Del Pizzo, S. Farina, A. Giaquinto, A. Lambertini, M. Menghini, S. Mokhtari, F. Ragazzola, S. Troisi, L. Vittuari

“…The impact of temperature variations on its growth has only recently been investigated in the field, although with destructive sampling methods. …”
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A novel mechanism and model of hydrogen isotope exchange in vacancy considering nuclear quantum effects by Qihang Liu, Fei Sun, Jipeng Zhu, Hai-Shan Zhou, Hongxiang Zong, Zhangcan Yang, Hong-Bo Zhou, Yasuhisa Oya, Yucheng Wu

“…Hydrogen isotope (HI) exchange has proven to be an effective method for T removal. However, the microscopic mechanisms, particularly the role of isotope effects, remain insufficiently understood. …”
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PIFRNet: Position Information Guided Feature Reconstruction Network for Salient Object Detection in Remote Sensing Images by Zhen Wang, Ruixiang Li, Xiaotian Wang, Nan Xu, Zhuhong You

“…Extensive experiments on three public RSI-SOD datasets demonstrate that our method achieves significant improvements over 36 state-of-the-art approaches, validating the effectiveness of each proposed module.…”
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PREDICTIVE MODELS FOR EARLY DETECTION OF PARKINSON’S DISEASE: A MACHINE LEARNING APPROACH by S. Jeyantha Jafna Juliet, D. Jasmine David, J. S. Raj Kumar, Angelin Jeba P., R. Golden Nancy, M. Selvarathi, T. Jemima Jebaseeli

“…When used to diagnose Parkinson's disease (PD), the proposed methods produce accuracy rates of 98.9% for Naive Bayes and 97.3% for Logistic Regression.…”
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Efficient Urban Tree Species Classification via Multirepresentation Fusion of Mobile Laser Scanning Data by Yinchi Ma, Peng Luan, Yujie Zhang, Bo Liu, Lijie Zhang

“…However, MLS-based classification faces challenges, such as intricate canopy structures, incomplete point clouds from urban occlusions, and intraspecies variations. This study presents tree morphology multirepresentation fusion network, integrating 3-D point cloud data with 2-D projections for enhanced tree species classification. …”
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Dual-stream detection and segmentation framework for vision based unmanned ground vehicle pothole perception on unstructured roads by Chenyuan He, He Yang, Zhouyu Zhang, Hai Wang, Yingfeng Cai, Long Chen, Can Zhong, Yiqun Zhang

“…Specifically, the detection stream adopts an enhanced YOLOv10+ network equipped with a frequency-aware fusion module (FreqFusion) in the neck to improve semantic–spatial alignment and robustness to texture variation. The segmentation stream introduces GAL-DeepLabv3+plus, which integrates a Dense Atrous Spatial Pyramid Pooling (DenseASPP) module and a Graph Attention Layer (GAL) into the standard DeepLabv3+ architecture, thereby enhancing contextual reasoning and boundary refinement. …”
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Paradigm predictive analysis of two-phase Eyring–Powell fluid flow over a vertical stretching sheet with temperature-dependent viscosity by multilayer neural networks by Zahoor Shah, Hamza Iqbal, Waqar Azeem Khan, Taseer Muhammad, Muhammad Shoaib

“…PDEs are converted into nonlinear ODEs with similarity transformations, which are solved using the Adam method in Mathematica with varied physical parameters to generate a reference dataset. …”
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Coupled Lake‐Atmosphere‐Land Physics Uncertainties in a Great Lakes Regional Climate Model by William J. Pringle, Chenfu Huang, Pengfei Xue, Jiali Wang, Khachik Sargsyan, Miraj B. Kayastha, T. C. Chakraborty, Zhao Yang, Yun Qian, Robert D. Hetland

“…Abstract This study develops a surrogate‐based method to assess the uncertainty within a convective permitting integrated modeling system of the Great Lakes region, arising from interacting physics parameterizations across the lake, atmosphere, and land surface. …”
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In situ high-temperature Raman spectroscopy for online EAF slag analysis by Bohong Zhang, Hanok Tekle, Ronald J. O'Malley, Jeffrey D. Smith, Farhan Mumtaz, Jie Huang

“…Real-time monitoring of slag chemistry is critical for optimizing Electric Arc Furnace (EAF) steelmaking operations, where dynamic variations in slag composition directly influence slag foaming, refractory degradation, and thermal efficiency. …”
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